Biology subjects

Ma, Y.

Publications and source records attributed to Ma, Y..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Biosynthesis of bisbenzylisoquinoline alkaloids

Bisbenzylisoquinoline alkaloids (bisBIAs) are pharmacologically valuable plant metabolites with complex stereochemical architectures, yet the catalytic principles governing their assembly have remained largely unclear. Here, we elucidate the enzymatic pathway to cyclic bisBIAs and uncover a non-canonical redox-mediated mechanism for post-assembly stereochemical control. We identify cytochrome P450 enzymes that catalyze regioselective oxidative dimerization and macrocyclization of benzylisoquinoline monomers, establishing the macrocyclic scaffold. Subsequent stereochemical specification is achieved by a paired oxidase-reductase module that selectively epimerizes a single stereocenter through a transient imine formation, converting (R,S)-configured intermediates to (S,S)-products. Reconstitution of the pathway in yeast enabled production of both native bisBIAs and non-natural analogs, demonstrating pathway modularity and engineering potential. These results establish the biochemical principle underlying bisBIA biosynthesis and provide a framework for programmable biosynthesis of these complex natural products.

biochemistry↗

bioRxiv2026

TSC2 is a stress granule suppressor

Stress granules (SGs) are dynamic, membrane-less ribonucleoprotein assemblies that form through liquid-liquid phase separation to prioritize stress-survival proteostasis. Through reanalysis of a Drosophila genome-wide RNAi screen, we identified a set of conserved SG suppressor genes and validated the top candidate, Tsc2, in both mouse and human cell lines. We illustrate that the complete loss of Tsc2 leads to spontaneous, canonical, and translation-dependent SGs driven by mTORC1 hyperactivation in mouse embryonic fibroblasts (MEFs). In addition, the Tsc2-deficient MEFs also sensitized to endoplasmic reticulum stress, delaying SG clearance. In human cell lines, the siRNA-mediated partial reduction of TSC2 in U2OS cells, and in human tuberous sclerosis patient fibroblasts, does not induce spontaneous SGs. Instead, the sensitivity to ER stress, translation perturbation, and delay in clearance correlate with the remaining levels of TSC2, suggesting that TSC2 functions as a threshold-dependent regulator of SG assembly. Together, our findings provide a comprehensive list of novel conserved SG regulators and establish TSC2 as a key regulator of SG dynamics.

cell biology↗

bioRxiv2026

Hypertension is related to a slower radiotracer removal from lateral ventricles

BackgroundImpairment of brain waste removal contributes to Alzheimers disease etiology and progression. Although hypertension is a risk factor for dementia, little is known about how it affects measures of clearance in human brain. MethodsCross-sectional (n=159) and longitudinal (n=94) analysis of the relationship between blood pressure (BP) and brain clearance. The estimate of brain clearance was measured using positron emission tomography (PET) as the rate of radiotracer (MK-6240) efflux from the lateral ventricles in the 10-30-minute window after tracer injection. We also examined cerebral blood flow, PET-derived tau deposition in the medial temporal lobe, cognition and plasma biomarkers of neurodegeneration. At baseline we compared participants with (n=88) and without (n=71) hypertension. For longitudinal analyses we defined two groups based on systolic BP trajectories from baseline to follow-up: as long-term controlled (n=76) or uncontrolled BP (n=18). ResultsAt baseline, subjects with hypertension had lower ventricular clearance than normotensive controls (Cohens d=0.53, p=0.001). Over the course of the observation period (median 1.85 years) subjects in the uncontrolled BP group experienced a steeper reduction in clearance rates ({beta}=-5.88) than subjects in the controlled BP group ({beta}=-0.81, interaction p=0.039). ConclusionsOur study suggests that hypertension impairs brain clearance of fluids.

neuroscience↗

bioRxiv2026

Large-scale activity analysis of gut prophages reveals significantly active lineages in the human gut

Prophages dominate the human gut virome and their transition from lysogeny to lytic replication profoundly affects gut microbial community structure. However, the global activity landscape of gut prophages remains largely uncharted. Here, we developed a workflow to assess prophage activity across more than 30,000 gut bacterial isolates cultured in vitro under standard conditions. Using this approach, 4,033 prophages, corresponding to a small fraction (7.5%) of the overall prophage reservoir, were detected as active, indicating a high-lysogeny, low-activity landscape. Prophage activity varied markedly across host taxa, with Bacillota exhibiting notably elevated active rates. Active prophages derived from 183 viral families (vFAMs), 55 of which were assigned as significantly active (SA-vFAMs), including: SA-vFAM7, a novel, hyper-prevalent lineage with expanded host range into Tannerellaceae and substantial intra-lineage diversity; and Candidatus Mubacviridae (SA-vFAM1), a newly defined, hankyphage-inclusive, highly active Mu-like transposable phage family infecting Bacteroidales, characterized by conserved MuA-MuB operons and cross-family host range. Together, this work provides a large-scale, activity-integrated atlas of human gut prophages, demonstrating that prophage activity is driven by both host phylogeny and viral lineage identity, and establishing a foundational resource for understanding prophage ecology.

microbiology↗

bioRxiv2026

PromptBio-Bench: Benchmarking LLM-based Bioinformatics Agents for End-to-End Data Analysis

Large language model (LLM)-based agents hold transformative potential for automating bioinformatics workflows; however, systematic evaluations of their capabilities remain limited, hindering a clear assessment of their readiness for real-world application. We introduce PromptBio-Bench, a comprehensive evaluation suite of 244 expert-curated tasks spanning bioinformatics and data science at varied difficulty levels, and an evaluation framework for structured file comparison and scoring against expert reference answer files. Evaluation of three state-of-the-art bioinformatics agents revealed comparable performance between Biomni and ToolsGenie, with all agents showing a marked decline in accuracy as task difficulty increased. As foundation models and agent frameworks continue to evolve, PromptBio-Bench provides a valuable benchmark infrastructure for systematically tracking progress in agentic bioinformatics.

bioinformatics↗

bioRxiv2026

Coordinated synthesis of double-stranded DNA by a dual reverse transcriptase immune system

Defense-associated reverse transcriptase (DRT) systems mediate antiviral immunity through distinct modes of cDNA synthesis: Class 1 DRTs catalyze untemplated synthesis, whereas Class 2 DRTs polymerize noncoding RNA-templated products. However, how these distinct modes drive defense remains unclear. Here, we report that DRT3 immunity arises when Class 1 and Class 2 RT activities cooperate to produce self-complementary double-stranded DNA (dsDNA). DRT3a uses a 5'-ACACAC-3' RNA template to synthesize poly-(dTdG) repeats, whereas DRT3b synthesizes poly-(dCdA) repeats without any nucleic acid template. Cryo-electron microscopy reveals that DRT3b forms a hexamer and uses active-site-adjacent residues as deoxyadenosine and deoxycytidine gates to enforce alternating nucleotide addition, representing a unique example of amino acid-templated DNA polymerization. DRT3 is toxic in cells lacking RecBCD, implicating host recombination machinery in limiting dsDNA accumulation, and the phage-encoded RecBCD inhibitor Gam triggers DRT3-mediated abortive infection. These findings reveal how two polymerases with distinct templating strategies generate complementary DNA for defense.

microbiology↗

bioRxiv2026

AM-DMF-SCP-pro: An Ultrafast and Streamlined Nanolitre-Scale Lab-on-a-Chip Platform for Single-Cell Proteomics and Tumor Microenvironment Profiling

Single-cell proteomics (SCP) remains constrained by slow sample preparation and background interference in low-input, multistep workflows, limiting its broader practical use in complex biological samples. Here we report AM-DMF-SCP-pro, a streamlined active-matrix digital microfluidic workflow that enables rapid on-chip lysis and digestion in 6 nL droplets within a closed nanolitre-confined microenvironment. AM-DMF-SCP-pro reduces total sample-preparation time to as little as 30 min, including a 15 min digestion step, while maintaining quantitative reproducibility and digestion performance. Systematic optimization of mass spectrometry acquisition and nanolitre-scale digestion conditions enables deeper, more sensitive and lower-background proteome profiling from ultra-low peptide inputs. In murine tumor samples, AM-DMF-SCP-pro reliably resolves immune and tumor compartments, identifies treatment-associated tumor cell states and enables quantitative analysis of neutrophil-associated proteomic signatures. These results establish AM-DMF-SCP-pro as a practical workflow for rapid, low-background single-cell proteome profiling in complex biological samples.

systems biology↗

bioRxiv2026

A grid-like basis for affective space in human ventromedial prefrontal cortex

Human emotional experiences vary widely in everyday life, yet they are systematically organized within a continuous affective space defined by valence and arousal. Although this circumplex organization has shaped decades of research, its neural implementation remains unclear. Here, we asked whether abstract emotion concepts are encoded using grid-like coordinate principles in the human brain. During fMRI, participants tracked trajectories through affective space conveyed through morphs of facial expressions and sequences of phrases. We found that ventromedial prefrontal cortex (vmPFC) encoded affective space with robust hexadirectional modulation characteristic of grid-like coding. This coordinate representation generalized across stimulus modalities, indicating abstraction beyond perceptual features. The grid-like signal reflected a stable metric organization of emotion concepts independent of overt behavior, whereas distance-related signals in vmPFC predicted trial-by-trial affective judgements. Together, these findings suggest that emotion knowledge is structured by a grid-like coordinate system in the human brain that can support predictive inference and flexible decision-making.

neuroscience↗

bioRxiv2026

Distinct HPO axis responses and ovarian aging trajectories to chronic unpredictable mild stress in reproductively young versus middle-aged female mice

Psychosocial stressors are key contributors to ovarian functional decline. Chronic unpredictable mild stress (CUMS) is widely used to model stress-induced premature ovarian insufficiency (POI) in mice; however, current animal models do not adequately reflect middle-aged women, who represent a key population exposed to chronic psychosocial stress, nor do they capture the dynamic progression toward POI. Here, female C57BL/6 mice aged 2 or 6 months were subjected to CUMS for 8 or 12 weeks. Estrous cyclicity, endocrine profiles, ovarian histology, and transcriptomic changes in HPO axis-related tissues were systematically analyzed. After 8 weeks of exposure, 2-month-old mice exhibited impaired pituitary responsiveness to estradiol negative feedback, as evidenced by dysregulated FSH secretion, indicating reduced stress tolerance compared with 6-month-old mice. Following 12 weeks of CUMS exposure, both age groups showed significant reductions in ovarian size and follicle numbers across all developmental stages. These findings demonstrate that CUMS induces an age-dependent progression toward POI, with short-term exposure eliciting compensatory phases preceding overt ovarian insufficiency, accompanied by distinct endocrine and reproductive alterations and differential responsiveness of the HPO axis. Transcriptomic analyses revealed age-dependent stress responses: ovaries of 2-month-old mice displayed marked activation of inflammatory and immune-related pathways, whereas 6-month-old mice showed sustained upregulation of protein kinase-related signaling networks. Notably, the 6-month-old CUMS model more closely recapitulates stress-associated reproductive aging in adult women. In briefCUMS has been widely used to establish mouse models of psychosocial stress-induced POI. However, current animal models do not adequately reflect middle-aged women, who represent a key population exposed to chronic psychosocial stress, nor do they capture the dynamic progression toward premature ovarian insufficiency (POI). In this study, we demonstrate that different durations of CUMS exposure induce distinct stages of ovarian dysfunction in both young and middle-aged mice, with short-term exposure driving age-dependent compensatory phases and prolonged exposure leading to overt POI, both accompanied by divergent endocrine and reproductive alterations, alongside age-dependent changes in HPO axis responsiveness to CUMS. Notably, the 6-month-old CUMS model shows greater clinical relevance in recapitulating chronic psychosocial stress and stress-related reproductive aging in adult women.

physiology↗

bioRxiv2026

Scalable, Generalizable, and Uncertainty-Aware Integration of Spatial Multi-Omics Across Diverse Modalities and Platforms with SCIGMA

Recent advances in spatial omics technologies have enabled simultaneous profiling of transcriptomic, proteomic, epigenomic, metabolomic, and imaging data at high spatial resolution, offering unprecedented opportunities to dissect tissue complexity. However, integrating these diverse and large-scale spatial multi-modal datasets remains a major computational challenge. We present SCIGMA, a scalable and generalizable deep learning framework for spatial multiomics integration. SCIGMA introduces a novel uncertainty-aware contrastive learning objective and multi-view graph neural networks to preserve modality-specific signals while learning biologically meaningful joint representations. Unlike existing methods, SCIGMA provides spatially resolved uncertainty estimates, improving interpretability and identifying regions of biological or technical heterogeneity. SCIGMA is the first spatial multi-omics method to support integration of up to five modalities--as demonstrated on Spatial-Mux-Seq data--and its modular framework is extensible to future technologies with even more modalities. It also scales to over one million spatial locations, enabling analysis of ultra-high-resolution datasets such as VisiumHD and Xenium Prime. We evaluated SCIGMA across 19 datasets spanning 8 modalities, 10 tissues, and 9 platforms. On benchmarkable datasets, SCIGMA outperformed existing methods in spatial domain detection, modality preservation, feature reconstruction, and reproducibility. Across applications, it uncovered biologically meaningful structures, refined spatial domains, and modality-specific regulatory programs, while its uncertainty estimates revealed tissue regions with potential biological or technical variation. Together, SCIGMA provides a robust, flexible, and future-ready solution for scalable spatial multi-modal integration.

bioinformatics↗

bioRxiv2026

Detergent-Free Nuclear-Cytoplasmic Fractionation Enables Spatially Resolved PELSA for Enhanced Nuclear Drug Target Identification

Accurate identification of drug target proteins remain major challenges in proteomics-based target discovery, particularly for low-abundance nuclear proteins that are difficult to detect because of the complexity of whole-cell lysates. Here, we developed a detergent-free nuclear-cytoplasmic fractionation strategy compatible with peptide-centric local stability analysis (PELSA), which markedly improves detection of nuclear drug targets. Using K562 cells, we demonstrated that mild detergent-free fractionation enables high-fidelity nuclear-cytoplasmic separation with minimal cross-contamination. When coupled with PELSA, this workflow significantly increases the number of detected nuclear targets relative to whole-cell analysis. Benchmarking with well-characterized nuclear drugs, including the histone deacetylase inhibitor panobinostat and the RNA polymerase II inhibitor -amanitin, our results showed improved identification of canonical nuclear targets. Broad profiling of staurosporine target further revealed expanded kinase target coverage by combining the results of nuclear and cytoplasmic fraction, with the CLK family kinases detected exclusively in the nuclear fractions. Additionally, we showed that PELSA can also be performed on intact nucleus level. Collectively, these findings establish detergent-free nuclear-cytoplasmic fractionation-PELSA as a robust and scalable strategy for spatially resolved drug target identification, improving sensitivity for nuclear and low-abundance proteins.

biochemistry↗

bioRxiv2026

Single-cell carbon storage dynamics drive conditional fitness in microbes

Microbes frequently encounter fluctuating environments, requiring dynamic energy management strategies for survival. While carbon storage polymers like polyhydroxybutyrate (PHB) are ubiquitous across bacterial taxa, their precise ecological advantage remains poorly understood.1 Here we show that carbon storage drives conditional fitness during environmental transitions. Using a high-throughput single-cell microfluidic platform, we tracked tens of thousands of Cupriavidus necator cells under precisely controlled carbon and nitrogen fluctuations. We found that PHB provides no advantage under nutrient abundance but becomes decisive at starvation boundaries: during carbon starvation, it enables [~]30% more progeny before arrest; during recovery from nitrogen starvation, it shortens lag and accelerates regrowth. Strikingly, at the single-cell level, PHB granules are inherited in an asymmetric, all-or-nothing fashion, concentrating resources into specific lineages to overcome the discrete energetic threshold required for cell division. Despite this single-cell variance, at the population level, PHB fractions robustly return to a common setpoint after nutrient shifts--a homeostatic behavior consistent with integral feedback control. These findings reveal that while PHB does not increase the basal exponential growth rate, it confers a distinct fitness advantage by prolonging the proliferative phase during nutrient depletion and facilitating successful recovery from starvation, explaining the evolutionary persistence of carbon storage in environments with pulsed resource availability.

microbiology↗

bioRxiv2026

Protein Language Models Encode Evolutionary Grammar but Conflate Topological and Thermodynamic Phases

How a one-dimensional sequence encodes a dynamic thermodynamic ensemble rather than a static geometry remains a fundamental biophysical challenge. While protein language models achieve high structural accuracy from single sequences, it remains unclear whether they internalize physical folding principles or merely capture evolutionary statistical correlations. We investigate this representational capacity by analyzing the latent manifold of ESM-2 across 11068 proteins, focusing on fundamental exceptions to the Anfinsen assumption: intrinsically disordered, fold-switching, and knotted proteins. We demonstrate that ESM-2 integrates out microscopic backbone geometry during feature extraction. It instead forms a macroscopic sequence grammar manifold that separates random sequences while ordering biological proteins along physicochemical composition gradients. Consequently, the model exhibits topological aliasing. It conflates these physically distinct categories because they frequently share overlapping sequence statistics despite divergent three-dimensional topologies. A region-replacement experiment establishes this aliasing as an intrinsic characteristic rather than an artifact of sequence dilution, and a structure-aware control model (SaProt) demonstrates that explicit structural tokens partially alleviate topological blindness for static anomalies while failing to resolve multi-state thermodynamic phases. Furthermore, local curvature analysis reveals class-invariant geometric turbulence that homogenizes microscopic details while preserving macroscopic distinguishability. ESM-2 therefore functions as an evolutionary grammar compressor rather than a microscopic threedimensional geometry encoder, imposing defined boundaries on tasks requiring high-precision geometric awareness and necessitating integration with explicit physical constraints.

biophysics↗

bioRxiv2026

Coronavirus envelope protein drives iron sensing disorder by hijacking the TAp73-FDXR axis

Iron overload is increasingly recognized as a critical contributor to coronavirus pathogenesis1, yet the underlying induction mechanisms remain unclear. Here, we uncover a fundamental pathway by which coronavirus drives IRP1 RNA-binding activity to induce iron accumulation2 via targeting the TAp73-FDXR axis. Specifically, coronavirus infection represses transcription of FDXR (encoding the key rate-limiting enzyme in host iron-sulfur cluster synthesis3), thereby impairing host iron-sulfur cluster generation to trigger the functional conversion of the cytosolic aconitase 1 (ACO1) into iron-regulatory protein 1 (IRP1)4, ultimately leading to the hosts persistently false perception of iron deficiency. We identify TAp73 as the primary transcription factor governing FDXR expression, and demonstrate that the coronavirus envelope protein (CoV-E) orchestrates TAp73 nuclear export. Subsequently, CoV-E binds TAp73 through a critical valine residue within its C-terminal PBM domain, inducing the K48-linked ubiquitination and proteasomal degradation of TAp73. Furthermore, we developed a CoV-E-targeting molecule, DPTP-FC, which blocks CoV-E-TAp73 interaction via forming steric hindrance and effectively alleviates iron accumulation and tissue damage caused by PEDV, PDCoV, and SARS-CoV-2 infection. Our study reveals the central role of the TAp73-FDXR axis in CoV-induced iron accumulation, highlighting CoV-E as an attractive antiviral target and DPTP-FC as a promising therapeutic candidate.

microbiology↗

bioRxiv2026

High-channel-count neural recording and stimulation platform with 5,376 simultaneous recording channels

Advancing neural interfaces requires large-scale, high-density recording technologies capable of capturing full-spectrum neural activity across cortical and subcortical regions. Here, we present a scalable approach to integrate neural electrodes with advanced application-specific integrated circuits (ASICs). Specifically, we custom-designed an ASIC with 5,376 simultaneous channels, each sampling at 20 kS/s and enabling >1.3 Gb/s total data streaming throughput. The ASIC incorporates in-pixel amplification, time-division multiplexed ADCs, and on-chip stimulation capabilities, ensuring precise signal acquisition with minimal power consumption while maintaining a low noise level of 5.5 {micro}Vrms. We further developed an interconnect strategy using gold bump bonding, which allows for high-density integration of the flexible probe and rigid chip. We demonstrate the capacity of this platform through the integration with a flexible ECoG array. The resulting device allows for the high-resolution mapping of in vivo field potentials on the cortical surfaces of rat brains, supported by the precise localization of evoked sensory activities. These results prove an effective approach towards highly integrated neural interfaces with applications in brain-computer interfaces, neuroprosthetics, and large-scale functional brain mapping.

bioengineering↗

bioRxiv2026

Cholecystokinin released somatodendritically from dopamine neurons broadly alters synaptic strength across the ventral tegmental area

Neuropeptides are found in nearly every brain neuron, and can modulate behaviors by regulating neuronal excitability, synaptic transmission, and plasticity. In contrast to the canonical view of neuropeptide release from nerve terminals, we previously reported the somatodendritic release of cholecystokinin (CCK) from ventral tegmental area (VTA) dopamine (DA) neurons. Release of CCK occurs during modest depolarization of VTA DA cells, and by activating CCK2Rs, potentiates synaptic transmission from GABAergic afferents. Here, recording from dopamine neurons in acute midbrain slices from male and female mice, we examined how somatodendritic release of CCK regulates synaptic plasticity and the extent of its influence. Depolarization of a dopamine neuron induced long-term potentiation (LTP) at GABAergic synapses, and in parallel somatodendritic CCK release produced long-term depression (LTD) at glutamatergic synapses. CCK-induced LTP persisted when postsynaptic G protein signaling in dopamine neurons was blocked, suggesting that CCK likely acts at GABAergic presynaptic terminals. Activation of kappa opioid receptors prevented CCK-dependent LTP of GABAergic synapses, indicating interaction between these two neuromodulatory signaling pathways in VTA. Surprisingly, depolarization of one dopamine neuron potentiated synapses onto both the depolarized neuron and neighboring dopamine neurons located up to [~]100 {micro}m away, indicating substantial spread of CCK signaling and synaptic modulation within the VTA region. Taken together, our findings demonstrate that somatodendritic CCK release bidirectionally coordinates synaptic strength across dopamine neurons, identifying a peptide-mediated feedback mechanism that shapes VTA circuit function. Significance StatementDopamine neurons in the ventral tegmental area (VTA) play central roles in reward, motivation, stress responses, and feeding behavior. While fast synaptic inputs regulate dopamine neuron firing on fast timescales, less is known about how slower neuromodulatory signals shape these circuits. We show that somatodendritic release of the neuropeptide cholecystokinin from dopamine neurons coordinately alters both inhibitory and excitatory synaptic strength and influences neighboring neurons within the VTA. This peptide-mediated feedback mechanism operates over a broader spatial scale than classical synaptic transmission and is regulated by kappa opioid signaling. These findings reveal how local peptide release can reshape dopamine circuit function and may contribute to changes in reward processing and feeding behavior.

neuroscience↗

bioRxiv2026

Cell type-specific gene regulatory network inference from single cell transcriptomics with ctOTVelo

Inferring gene regulatory networks (GRNs) from gene expression is a crucial task for understanding functional relationships. Gene expression data (transcriptomics) provide a snapshot of gene activity, encoding information about gene regulatory relationships. However, gene regulation is a dynamic process, modulating across time and with different cell types. Temporal GRN inference methods aim to capture these dynamics by utilizing time-stamped transcriptomics, gene expression data of similar samples captured across discrete timepoints, or pseudotime transcriptomics, computationally ordering cells based on an inferred trajectory. These methods can estimate constant or temporal gene regulatory relationships, but may not capture finer, cell type specific relationships. We propose ctOTVelo, an extension to our previous work to account for cell type specificity during GRN inference. ctOTVelo incorporates cell type labels or proportions when inferring the GRN from single cell transcriptomics data. Our methods achieve state-of-the-art performance in GRN prediction in time-stamped and pseudotime-stamped transcriptomics. Furthermore, ctOTVelo is able to generate cell type specific GRNs, allowing cell type resolution analysis of gene regulatory relationships.

genomics↗

bioRxiv2026

Orthologous synteny provides robust structural evidence for the ancestral angiosperm ε-WGD

The ancestral angiosperm whole-genome duplication ({varepsilon}-WGD) is a pivotal yet contentious event that has long been debated. A recent study refuted its occurrence based on deviations from expected retention patterns of dosage-sensitive genes. Here, we provide both structural (orthologous synteny) and phylogenetic (subgenome-aware) evidence to revisit this debate. With improved annotation of the Ginkgo genome, we uncover a clear 1:2 orthologous synteny ratio between Ginkgo and early-diverging angiosperms (Amborella and Aristolochia), which lack lineage-specific WGDs. Subgenome-aware phylogenomic analyses further demonstrate that the Amborella/Aristolochia subgenomes diverged after the gymnosperm-angiosperm split but before the radiation of extant angiosperms. Together, these findings provide direct structural evidence for an ancestral angiosperm tetraploidization in the early Jurassic, following divergence from gymnosperms. We argue that the recent refutation of the {varepsilon}-WGD relies on restrictive assumptions regarding ploidy level and duplicate retention that may not hold for deep-time polyploidy events. Our results provide a robust resolution to this long-standing debate and reaffirm the {varepsilon}-WGD as a shared synapomorphy of extant angiosperms.

evolutionary biology↗